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尚靖桓 Jinghuan ShangI'm a Ph.D. candidate in the Department of Computer Science at Stony Brook University, working with Prof. Michael Ryoo, as a part of CV Lab at Stony Brook. I received my Bachelor's degree from IEEE Honored Class at Shanghai Jiao Tong University (SJTU) in 2018, with honor from Shanghai. Research interest: Representation Learning, Robotics, and Computer Vision. Specifically, I find good visual representations for robots to perform visual tasks under reinforcement learning and imitation learning settings. [CV][GitHub] Email: jishang [at] cs &dot& stony brook %dot% edu |
2022/09 - 3DTRL and Study on SSL+RL are accepted to NeurIPS 2022.
2022/09 - TRITON for robot sim2real is accepted to CoRL 2022.
2022/09 - StARformer for real robot is accepted to TPAMI. A cute ground mobility robot is able to continuously follow me purely by visual inputs.
2022/08 - Started a research internship at Motional.
2022/07 - StARformer is accepted to ECCV 2022. Local representations benefit long-term sequence modeling in vision-based RL.
2022/06 - Introducing 3D Token Representation Layer, a plug-and-play module for Transformer to learn viewpoint-agnostic representations.
2021/06 - Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?
2021/06 - Our paper on Third-Person Imitation Learning is accepted to IROS 2021.
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Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space
Jinghuan Shang, Srijan Das, and Michael S. Ryoo NeurIPS 2022 [Project Page] [Code -- Coming Soon] [arXiv] |
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Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?
Xiang Li, Jinghuan Shang, Srijan Das, and Michael S. Ryoo NeurIPS 2022 [arXiv] |
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Neural Neural Textures Make Sim2Real Consistent
, Jinghuan Shang, Xiang Li, and Michael S. Ryoo CoRL 2022 [Project Page] [Code -- Coming Soon] [arXiv] |
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StARformer: Transformer with State-Action-Reward Representations for Robot Learning
Jinghuan Shang, Xiang Li, Kumara Kahatapitiya, Yu-Cheol Lee, Michael S. Ryoo IEEE TPAMI, Special Issue on Transformer Models in Vision, 2022 [PDF] |
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StARformer: Transformer with State-Action-Reward Representations for Visual Reinforcement Learning
Jinghuan Shang, Kumara Kahatapitiya, Xiang Li, and Michael S. Ryoo ECCV 2022 [arXiv] [Code] |
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Self-Supervised Disentangled Representation Learning for Third-Person Imitation Learning
Jinghuan Shang and Michael S. Ryoo IROS 2021 [arXiv] [Talk] [Digest Slide] |
| 2018/08 | - Merit Scholarship from the Department of Computer Science at Stony Brook University |
| 2018/06 | - Outstanding graduate among all graduates from universities in Shanghai |
| 2016 | - 1st Prize in Shanghai Division of China Undergraduate Mathematical Contest in Modeling (CUMCM) |
| 2015-2017 | - 3 times of Academic Excellence Scholarship at Shanghai Jiao Tong University |
I love cooking.
I solve some algorithm problems in my spare time. Luckily got Top 10 in 2020 SBU ICPC Slection Contest. Here is my [Leetcode].
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